code: def create_conv_layer(
      use_fan_in_scaled_kernel: bool = False,
      multiplier: float = math.sqrt(2),
      **kwargs,
  ) -> tf.keras.layers.Conv2D:
      """Creates a convolutional layer.
  
      Args:
        use_fan_in_scaled_kernel: Whether to use a FanInScaledConv2D or a standard
          Conv2D layer.
        multiplier: Additional multiplier used only for FanInSclaedConv2D layer.
        **kwargs: Keyword arguments forwarded to the convolutional layers.
  
      Returns:
        The created convolutional layer instance.
      """
      if use_fan_in_scaled_kernel:
          return keras_layers.FanInScaledConv2D(
              multiplier=multiplier, **kwargs
          )
      else:
          return tf.keras.layers.Conv2D(**kwargs)
  
file_path: graphics/tensorflow_graphics/projects/gan/architectures_progressive_gan.py
imports: import math
  from typing import Callable, Optional, Sequence, Union
  import tensorflow
  import tensorflow_addons.layers.normalizations
  from tensorflow_graphics.projects.gan import keras_layers
label_desc: Use image node_id 3 for calling a global function with example usage: create_conv_layer(use_fan_in_scaled_kernel, multiplier) and returns: keras_layers, tf